Coronary 3D Model Assembly From Multi-Source Medical Images
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Solution Overview
Problem
Current medical procedures rely heavily on mental conversion of 2D angiogram images to 3D models, leading to inaccurate treatment selections and suboptimal patient care due to lack of detailed anatomical and procedural information.
Innovation Solution
A system that integrates multiple imaging modalities to create a 3D model of coronary vasculature, utilizing AI and machine learning to provide detailed anatomical insights, procedural guidance, and risk analysis, overlaying relevant information on angiogram data for clinicians.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 2D angiogram images are used for visualization, then the imaging system is simple and easy to operate, but the anatomical detail and 3D spatial understanding are insufficient
Solution Approach 1:
The patent transforms 2D angiogram images into 3D volumetric data by assembling multiple 2D images from different views. This dimensional transition enables clinicians to visualize coronary vasculature in three dimensions, improving anatomical detail and spatial understanding while maintaining the simplicity of the original imaging modality.
Solution Approach 2:
The system merges multiple 2D angiogram images captured from different views and angles into a single integrated 3D model. This combination process preserves the simplicity of individual 2D images while creating comprehensive 3D anatomical representation, resolving the contradiction between simplicity and detail.
2Reliability
If multiple imaging modalities are integrated to create 3D models, then anatomical accuracy and treatment planning are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system performs preliminary processing of multiple imaging modalities to create a 3D model before the actual treatment procedure. This pre-processing includes automatically assembling images from different sources, generating the 3D representation, and preparing treatment pathway models, thereby improving treatment planning accuracy without increasing real-time system complexity.
Solution Approach 2:
The patent creates a virtual 3D copy of the patient's coronary vasculature from multiple imaging modalities. This digital replica allows for accurate treatment planning and simulation without requiring complex real-time processing during the actual procedure, thus improving reliability while managing system complexity.
3Productivity
If 3D models are generated from multiple imaging sources, then treatment pathway analysis and risk assessment are enhanced, but image processing time and computational resources increase
Solution Approach 1:
The system generates the 3D model and analyzes treatment pathways in advance before the clinical decision is needed. By performing image processing and model generation preliminarily, the system enhances decision-making efficiency without adding significant time delay during critical procedural moments.
Solution Approach 2:
The patent incorporates feedback loops where the 3D model and treatment pathway analysis continuously improve based on imaging data. This feedback mechanism allows for iterative refinement of the model and treatment planning, enhancing productivity while managing processing time through efficient algorithms.
Data Source
AI summary
Example systems and techniques are disclosed that may determine a three-dimensional (3D) model of a coronary vasculature of a patient. An example system may include memory configured to store the 3D model and processing circuitry communicatively coupled to the memory. The processing circuitry may be configured to obtain first fluoroscopy imaging data from a first viewing angle and obtain second fluoroscopy imaging data from a second viewing angle. The processing circuitry may be configured to determine the 3D model of the coronary vasculature of the patient based on the first fluoroscopy imaging data and the second fluoroscopy imaging data. The processing circuitry is configured to obtain additional imaging data from one or more imagers other than a fluoroscopy imager and update the 3D model based on the additional imaging data. The processing circuitry may be configured to output for display a representation of the 3D model.